Tensor product-based model transformation approach to tower crane systems modeling

This paper presents the application of the tensor product (TP)-based model transformation approach to produce Tower CRrane (TCR) systems models. The modeling approach starts with a nonlinear model of TCR systems as representative multi-input-multi-output controlled processes. A linear parameter-varying model is next derived, and the modeling steps specific to TP-based model transformation are proceeded to obtain the TP model. The TP model is tested on TCR laboratory equipment in two open-loop scenarios considering chirp signals and pseudorandom binary step signals applied to the three model inputs (control inputs). The nonlinear and TP model outputs in the two scenarios are the payload position, the cart position, and the arm angular position. The nonlinear and TP model outputs are collected, measured, and compared. The simulation results prove that the derived TP model approximately mimics the behavior of the nonlinear model; both system responses and numerical approximation errors are illustrated.